Computer-assisted operator control of hydraulic machinery requires stable, smooth machine response. Danko U.S. patent application Ser. No. 10/488,011, Publication No. 20040267404, “referenced Danko '404” hereinafter, entitled “Coordinated joint motion control system”, the entire disclosure of which application is hereby incorporated herein by reference thereto, discloses a coordinated joint motion control system for hydraulic machinery and the like. The disclosed control system employs a software-based kinematics reconfiguration system to assist the operator with various tasks. Danko '404's disclosure includes a differential, forward-prediction kinematics solution for adjusting the as-built machine hardware kinematics to an as-desired kinematics which provides desirable, reference actuator velocities and can yield a resultant motion trajectory that is well suited for the task specified. The systems and methods disclosed in Danko '404 are believed useful for their intended purposes, but, as is understood by the present invention the do not address the question of how to compensate for imperfect control system components.
Implementation of kinematics transformation from a virtual model in the digital domain to a real world tool trajectory is a difficult task because of the reliance on imperfect mechanical sensors and actuators. Energy loss reduction is a significant consideration for heavy equipment, mobile hydraulics control systems for excavators and the like may employ simplified control loops having higher energy efficiencies than do other control systems, for example hydraulic robot control systems. However, response time and precision may be compromised in such simplified hydraulic control loops. Generally, it is to be expected that the load-dependent valve and hydraulics control response characteristics will be non-linear. What are known as “measured valves” have been proposed to linearize the control valves and eliminate load-dependency by applying closed control loops around the valves. In Danko '404 a drawback of this approach, is that the hydraulic circuit may not effectively and timely apply the desired control velocity to the machine elements or links, owing to hydraulic flow inertia or pressure deficiencies that may arise.
Pursuant to the present invention it can be understood that it would be desirable to have accurate position information regarding the moving machine elements and especially regarding the end effector or tool. Further, it is an understanding of the invention that such position information for a given point in time and provided continuously throughout machine operation could be useful in enhancing control system performance.
A number of solutions have been proposed to the general problem of system identification i.e. determination of a system space-state at a given point in time from a noisy observation signal. For example Kalman, R. E., in “A New Approach to Linear Filtering and Prediction Problems,” Journal of Basic Engineering, 82 (Series D), 1960, pp. 35-45, describes an iterative method for developing a state-space system model during the solution. Various methods for identifying a causal linear or non-linear system are given by Schetzen, M., The Volterra and Wiener Theories of Nonlinear Systems, John Wiley and Sons, 1980, including convolution and Volterra series-based solutions.
Hypothetically, it might be possible to construct a priori a multi-variable, nonlinear machine model, at least for an unloaded machine, that could predict the motion of the machine under arbitrary control of all actuators. A non-iterative, Volterra-series, linear or non-linear, multi-variate system identification method could be applied. A drawback of such methods is that they may be computationally too extensive to be effectively used in embedded real-time control applications, where model computation time is significantly limited. A priori system model developments are described by Juang, J.-N. and Phan, M. in “Identification of System, Observer, and Controller from Closed-loop Experimental Data,” Journal of Guidance, Control, and Dynamics, Vol. 17, No. 2, January-February 1994, pp. 91-96. and by Phan et al. in “Improvement of Observer/Kalman Filter Identification (OKID) by Residual Whitening,” Journal of Vibrations and Acoustics, Vol. 117, April 1995, pp. 223-238. An observer-controller identification method from measurements under closed-loop control is given by Juang and Phan [1994]. A state-space dynamic system model identification from measured input-output data processed first as observer Markov parameters is described by Phan et al., “Markov Parameters in System Identification: Old and New Concepts,” Structronic Systems: Smart Structures, Devices, and Systems, Vol. 2, Tzou, H. S. and Guran A. (eds.), World Scientific, Singapore, 1997, pp. 263-293.
A direct, adaptive system identification approach is described by Phan et al. in “Unifying Input-Output and State-Space Perspectives of Predictive Control,” Department of Mechanical and Aerospace Engineering Technical Report No. 3044, Princeton University, September, 1998 for predictive control of a flexible and lightly damped system with complex dynamics. Such an adaptive/predictive state-space control system component may be identified in the presence of unknown disturbances from measurements, as demonstrated by Goodzeit, N. E. and Phan, M. Q. in “System and Periodic Disturbance Identification for Feedforward-Feedback Control of Flexible Spacecraft,” Proceedings of the 35th AIAA Aerospace Science Meeting and Exhibit, Reno, Nev., January 1997. Goodzeit N. E. and Phan point to advantages that may be obtained by simplifying a control compensation task by excluding responses to selected disturbances. Such methods can avoid the saturation of the adaptive control system with too many disturbance-corrupted signals and can be described as “clear-box” adaptive control methods. However, none of these proposals is entirely adequate to compensate for the mechanical inefficiencies that may arise in articulated hydraulic machinery under time- and task-variable, external loads.
The foregoing description of background art may include insights, discoveries, understandings or disclosures, or associations together of disclosures, that were not known to the relevant art prior to the present invention but which were provided by the invention. Some such contributions of the invention may have been specifically pointed out herein, whereas other such contributions of the invention will be apparent from their context. Merely because a document may have been cited here, no admission is made that the field of the document, which may be quite different from that of the invention, is analogous to the field or fields of the present invention.